Modern day consumers are confronted with numerous entertainment options and an immeasurable amount of available media content. Thousands of videos, songs, and articles are available to users through the Internet, television, and other gateways to media content. In such an environment, recommendation engines that suggest content to users have taken on increasing importance. Examples include media guidance applications and web sites that recommend movies, books, and other content to users based on user preference information.
Traditional systems often monitor a user's behavior (e.g., ongoing media selections) to gather preference information. Of course, another preferred source of user preference data is the user herself. Traditional systems sometimes allow a user to specify preference information directly, e.g., by filling out a questionnaire. However, new techniques for displaying user preference information and for receiving such information directly from a user remain highly desirable.